A simultaneous method for fuzzy memberships and rule optimization

Author

Tang, K.S. ; Chan, C.Y. ; Man, K.F.

Author_Institution

Dept. of Electron. Eng., City Univ. of Hong Kong, Hong Kong

fYear

1996

fDate

2-6 Dec 1996

Firstpage

279

Lastpage

283

Abstract

A new scheme to optimize an optimal fuzzy subsets and rules is proposed. The method is derived by using genetic algorithms where the genes of the chromosome are classified into two types of genes. These genes can be arranged in a hierarchical form and one type of the genes control the other type of genes. The effectiveness of this genetic formulation enables the fuzzy subsets and rules to be optimally reduced and yet, the system performance is well maintained. To justify this approach of fuzzy logic design, the proposed scheme is experimentally demonstrated by applying it to control a constant water pressure pumping system

Keywords

encoding; fuzzy control; fuzzy logic; fuzzy set theory; genetic algorithms; hierarchical systems; chromosome; constant pressure water pumping system; encoding; fuzzy control; fuzzy logic; fuzzy memberships; fuzzy rules; fuzzy subsets; genes; genetic algorithms; optimization; Biological cells; Control systems; DNA; Fuzzy control; Fuzzy logic; Fuzzy sets; Fuzzy systems; Genetic algorithms; Genetic engineering; Optimization methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Technology, 1996. (ICIT '96), Proceedings of The IEEE International Conference on

Conference_Location

Shanghai

Print_ISBN

0-7803-3104-4

Type

conf

DOI

10.1109/ICIT.1996.601590

Filename

601590